1. Field of the Invention
The present invention relates to the field of video signal processing, and, more particularly, to a system and method for rapidly tracking multiple faces.
2. Description of Related Art
With the advent of computer technologies, real-time face tracking has become an important issue in many applications including human computer interactions, video surveillance, teleconference, video retrieval, virtual reality, and so on. For example, in video communication application, face tracking is the key to reduce communication bandwidth by locating and transmitting only the fraction of a video frame that contains the speaker's face.
In the past, there are two most common methods used to implement a real-time face tracking system. The first one is based on the motion information and the second one is based on the skin color. If the motion information is used to detect and tract speaker's face, the basic assumption is the requirement of a known static background. However, if there are other motion objects besides the still observed faces, this approach will encounter severe problems to track correct faces.
On the other hand, the color-based method has the advantage that skin color is almost invariant against the variation in size, rotation, and partial occlusions of faces under constant lighting environment. Therefore, most current real-time systems for face detection and tracking are color-based. In this approach, image is segmented into skin and non-skin components, and a connected component algorithm is used to divide the input image into several closely connected skin regions thereby detecting faces from video sequences. However, in this approach, except faces, a lot of background objects, such as curtains, clothes, pictures, etc., also have the color similar to skin. Therefore, it is possible that a face can not be detected correctly due to these skin-color objects.
In order to efficiently separate the face regions from the complex backgrounds, a preferable approach is to use the hybrid information of color and motion. Then, the segmented regions are further verified to determine whether the correct faces are extracted form the remaining distracters. Such verification can be done by eigen-face analysis or geometrical analysis. However, these analyses are time-consuming and can not satisfy the real-time requirement for tracking faces. Furthermore, the detected faces are tracked by using correlation matching technique, which also requires a time-consuming searching operation, and the searching result may be invalid due to variation of the environmental light source. It is also difficult to determine whether the tracked face has been disappeared from a frame. Therefore, it is difficult to construct an effective real-time face tracking system with the above conventional skill.
Besides, for all above approaches, the most challenging problem is to track multiple-persons in real-time. In this problem, the tracked persons will appear or disappear in the video sequence in any time. For a desired system, it should have enough capabilities to identify and deal with the conditions when the tracked person disappears or one new person is coming. Therefore, the required hardware is very complex and the amount of data to be processed is very large, and thus, it is unsuitable in many applications. Accordingly, it is desirable to provide an improved system and a method for rapidly tracking multiple faces to mitigate and/or obviate the aforementioned problems.